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# <div align="center"><strong>vLLM</strong></div>
## 简介
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vLLM是一个快速且易于使用的LLM推理和服务库,使用PageAttention高效管理kv内存,Continuous batching传入请求,支持很多Hugging Face模型,如LLaMA & LLaMA-2、Qwen、Chatglm2 & Chatglm3等。
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## 暂不支持的官方功能
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- **量化推理**:目前支持fp16的推理和gptq,awq-int4推理,marlin的权重量化、kv-cache fp8推理方案暂不支持
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- **模块支持**:目前不支持Sliding window attention
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## 支持模型结构列表
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| 结构 | 模型 | FP16/BF16 | AWQ | GPTQ |
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| :------: | :------: | :------: | :------: |:------: |
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| LlamaForCausalLM      | Llama 3.1,Llama 3,Llama 2,Llama,Yi,Codellama,deepseek       | Yes | Yes | Yes |  
| QWenLMHeadModel       | QWen,Qwen-VL                                                | Yes | Yes | Yes |
| Qwen2ForCausalLM      | QWen2,QWen1.5,CodeQwen1.5                                   | Yes | Yes | Yes |
| ChatGLMModel          | glm-4v-9b,chatglm3,chatglm2                                 | Yes | No  | Yes |
| DeepseekV2ForCausalLM | DeepSeek-V2                                                 | Yes | No  | -   |
| BaiChuanForCausalLM   | Baichuan2,Baichuan                                          | Yes | Yes | -   |
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| BloomForCausalLM      | BLOOM                                                       | Yes | No  | Yes |
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| InternLMForCausalLM   | InternLM                                                    | Yes | No  | -   |
| InternLM2ForCausalLM  | InternLM2                                                   | Yes | No  | -   |
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| FalconForCausalLM     | falcon                                                      | Yes | No  | Yes |
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| TeleChat2ForCausalLM  | TeleChat2                                                   | Yes | No  | -   |
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| MiniCPMForCausalLM    | MiniCPM                                                     | Yes | No  | -   |
| MiniCPM3ForCausalLM   | MiniCPM3                                                    | Yes | No  | -   |
| MixtralForCausalLM    | Mixtral-8x7B,Mixtral-8x7B-Instruct                          | Yes | No  | -   |
| Qwen2MoeForCausalLM                 | Qwen2-57B-A14B,Qwen2-57B-A14B-Instruct        | Yes | No  | -   |
| LlavaForConditionalGeneration       | LLaMA,LLaMA-2,LLaMA-3                         | Yes | No  | -   |
| Qwen2VLForConditionalGeneration     | Qwen2-VL                                      | Yes | No  | Yes |
| MiniCPMV                            | MiniCPM-V                                     | Yes | No  | -   |
| Phi3VForCausalLM                    | Phi-3.5-vision                                | Yes | No  | -   |
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## 安装
vLLM支持
+ Python 3.9.
+ Python 3.10.
+ Python 3.11.
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+ Python 3.12.
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### 使用源码编译方式安装
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#### 编译环境准备
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提供2种环境准备方式:
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1. 基于光源pytorch2.4.1基础镜像环境:根据pytorch2.4.1、python、dtk及系统下载对应的镜像版本。
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2. 基于现有python环境:安装pytorch2.4.1,pytorch whl包下载目录:[https://cancon.hpccube.com:65024/4/main/pytorch](https://cancon.hpccube.com:65024/4/main/pytorch),根据python、dtk版本,下载对应pytorch2.4.1的whl包。安装命令如下:
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```shell
pip install torch* (下载的torch的whl包)
pip install setuptools wheel
```
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#### 源码编译安装
```shell
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git clone http://developer.hpccube.com/codes/OpenDAS/vllm.git # 根据需要的分支进行切换
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```
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安装依赖:
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```shell
pip install -r requirements-rocm.txt
```
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- 提供2种源码编译方式(进入vllm目录):
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```
1. 编译whl包并安装
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VLLM_INSTALL_PUNICA_KERNELS=1 python setup.py bdist_wheel 
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cd dist
pip install vllm*
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2. 源码编译安装
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VLLM_INSTALL_PUNICA_KERNELS=1 python3 setup.py install (若调试,可使用VLLM_INSTALL_PUNICA_KERNELS=1 python3 setup.py develop)
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```
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若需要添加git号,设置环境变量: export ADD_GIT_VERSION=1
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#### 运行基础环境准备
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1、使用上面基于光源pytorch2.4.1基础镜像环境
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2、根据pytorch2.4.1、python、dtk及系统下载对应的依赖包:
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- triton:[https://cancon.hpccube.com:65024/4/main/triton](https://cancon.hpccube.com:65024/4/main/triton/)
- flash_attn: [https://cancon.hpccube.com:65024/4/main/flash_attn](https://cancon.hpccube.com:65024/4/main/flash_attn)
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- lmslim: [https://cancon.hpccube.com:65024/4/main/lmslim](https://cancon.hpccube.com:65024/4/main/lmslim)
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#### 注意事项
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+ 若使用 pip install 下载安装过慢,可添加源:-i https://pypi.tuna.tsinghua.edu.cn/simple/
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## 验证
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- python -c "import vllm; print(vllm.\_\_version__)",版本号与官方版本同步,查询该软件的版本号,例如0.7.2;
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## Known Issue
-
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## 参考资料
- [README_ORIGIN](README_ORIGIN.md)
- [https://github.com/vllm-project/vllm](https://github.com/vllm-project/vllm)